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Comparison

agent-learning-kit vs auto-evaluator

Verdict

Pick agent-learning-kit if agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB; pick auto-evaluator if auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI.

Markdown twin · agent-learning-kit alternatives · auto-evaluator alternatives

GraphCanon updated 2w

agent-learning-kit logo

agent-learning-kit

future-agi/agent-learning-kit

★ 118pushed Aug 1, 2026
vs
auto-evaluator logo

auto-evaluator

rlancemartin/auto-evaluator

★ 1.1kpushed May 10, 2023

Trust & integrity

Signalagent-learning-kitauto-evaluator
Maintenance
Very active (0d since push)
As of 3w · github_public_v1
Dormant (1186d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
Published findings
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
agent-learning-kit trust reportauto-evaluator trust reportTrust methodology

Tagline

agent-learning-kit
Evaluation Framework for all your AI related Workflows
auto-evaluator
A lightweight evaluation tool for question-answering using Langchain

Stars

agent-learning-kit
118
auto-evaluator
1.1k

Forks

agent-learning-kit
43
auto-evaluator
92

Open issues

agent-learning-kit
6
auto-evaluator
3

Language

agent-learning-kit
Python
auto-evaluator
Python

Adopt for

agent-learning-kit
Agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB.
auto-evaluator
Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI.

Persona

agent-learning-kit
-
auto-evaluator
-

Runtime

agent-learning-kit
-
auto-evaluator
-

License

agent-learning-kit
Apache-2.0
auto-evaluator
-

Last pushed

agent-learning-kit
Aug 1, 2026
auto-evaluator
May 10, 2023

Categories

agent-learning-kit
Evaluation & Observability
auto-evaluator
Evaluation & Observability

Trust and health

Maintenance

agent-learning-kit
Very active (96%)
auto-evaluator
Dormant (18%)

Days since push

agent-learning-kit
0d
auto-evaluator
1186d

Open issues (now)

agent-learning-kit
6
auto-evaluator
3

Owner type

agent-learning-kit
Organization
auto-evaluator
User

OSV dependency advisories

agent-learning-kit
No lockfile (source not queried)
auto-evaluator
Published findings

Full report

agent-learning-kit
Trust report
auto-evaluator
Trust report

Shared compatibility

  • Python · agent-learning-kit: Python runtime · auto-evaluator: Python runtime

Choose agent-learning-kit if…

  • Tags unique to agent-learning-kit: ai-agents, ci-cd, ml.
  • When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed.
  • More recently updated (last pushed Aug 1, 2026).

When NOT to use agent-learning-kit

  • If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit.
  • When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
GitHubDetails

Choose auto-evaluator if…

  • Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering.
  • Use when you need a lightweight solution for testing question-answering capabilities of Langchain models.
  • More GitHub stars (1.1k vs 118) - visibility, not fit.

When NOT to use auto-evaluator

  • Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings.
  • If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature.
GitHubDetails

Explore

agent-learning-kit trust report →auto-evaluator trust report →Evaluation & Observability category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: agent-learning-kit 118 · auto-evaluator 1.1k (synced Aug 1, 2026).

Common questions

What is the difference between agent-learning-kit and auto-evaluator?
agent-learning-kit: Evaluation Framework for all your AI related Workflows. auto-evaluator: A lightweight evaluation tool for question-answering using Langchain. See the comparison table for live GitHub stats and shared categories.
When should I choose agent-learning-kit over auto-evaluator?
Choose agent-learning-kit over auto-evaluator when Tags unique to agent-learning-kit: ai-agents, ci-cd, ml; When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed; More recently updated (last pushed Aug 1, 2026).
When should I choose auto-evaluator over agent-learning-kit?
Choose auto-evaluator over agent-learning-kit when Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; More GitHub stars (1.1k vs 118) - visibility, not fit.
When should I avoid agent-learning-kit?
If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit. When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
When should I avoid auto-evaluator?
Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature.
Is agent-learning-kit or auto-evaluator more popular on GitHub?
auto-evaluator has more GitHub stars (1,105 vs 118). Stars measure visibility, not whether either tool fits your constraints.
Are agent-learning-kit and auto-evaluator open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to agent-learning-kit or auto-evaluator?
GraphCanon lists graph-backed alternatives at agent-learning-kit alternatives and auto-evaluator alternatives (agent-learning-kit markdown twin, auto-evaluator markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, agent-learning-kit or auto-evaluator?
agent-learning-kit: Very active. auto-evaluator: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for agent-learning-kit and auto-evaluator?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-learning-kit trust report; auto-evaluator trust report.

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